• Title/Summary/Keyword: Age Classification

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Development of Age Classification Deep Learning Algorithm Using Korean Speech (한국어 음성을 이용한 연령 분류 딥러닝 알고리즘 기술 개발)

  • So, Soonwon;You, Sung Min;Kim, Joo Young;An, Hyun Jun;Cho, Baek Hwan;Yook, Sunhyun;Kim, In Young
    • Journal of Biomedical Engineering Research
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    • v.39 no.2
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    • pp.63-68
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    • 2018
  • In modern society, speech recognition technology is emerging as an important technology for identification in electronic commerce, forensics, law enforcement, and other systems. In this study, we aim to develop an age classification algorithm for extracting only MFCC(Mel Frequency Cepstral Coefficient) expressing the characteristics of speech in Korean and applying it to deep learning technology. The algorithm for extracting the 13th order MFCC from Korean data and constructing a data set, and using the artificial intelligence algorithm, deep artificial neural network, to classify males in their 20s, 30s, and 50s, and females in their 20s, 40s, and 50s. finally, our model confirmed the classification accuracy of 78.6% and 71.9% for males and females, respectively.

A Study on Body Types of Mongolian Women (몽골 성인여성체형에 관한 연구)

  • 홍정민
    • Journal of the Korean Society of Costume
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    • v.51 no.6
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    • pp.167-176
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    • 2001
  • This study analyzes characterization and classification of body types of Mongolian women aged 18∼39 ages. The anthropometric measurements of the research subjects come up to a total of 23 items and are summarized as follows : 1. As the results of comparative analysis of the body measurements by age group, 16 items show a significant difference except shoulder height, thigh girth, neck base girth, back length shoulder length, sleeve length and weight. Both age group are considered to be of average weight but 25 to 39 age group were slightly greater than that of the 18 to 24 age group. 2. As the results of factor analysis, 4 factors such as the first factor on the obesity of body, the second factor on the vertical size of body, the third factor on the back length, the forth factor on the shoulder width and neck base girth were extracted. 3. As the results of classification based on the duster analysis, the body types were classified into 3 types in each age group. In each age group the most frequent body type is average stature and slightly thin type.

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Milk and Beverage Preference of College Students (대학생들에 대한 우유와 음료수의 기호성)

  • Kim, Hyun-Dae;Kim, Dong-Soo;Kim, Song-Suk
    • Journal of the Korean Society of Food Science and Nutrition
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    • v.23 no.3
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    • pp.420-428
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    • 1994
  • The purpose of this study was to determine relationship among the observed frequencies of 12 beverages selected by college men and women according to sex, age, race and academic classification and to estimate consumption of milk according to sex, age, race and academic classification. The instrument consisted of a check list and four questions. The sample of 282 subjects, 149 college men and 133 college women, was made by the accidental choice method. Observations occurred in the university center cafeteria at the dinner meal. The significant relationship s were sex and race in association with beverage selections by all subjects. The proportion of men in the distribution who selected regular , carbonated soft drinks and the proportion of white students who selected any of the carobnated soft drinks were the influencies. The result of the study indicated that carbonated soft drinks were the most preferred items followed by milk, water, iced tea, fruit juices, coffee, cocoa, and tea.

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A Study on Classification of Elderly Women's Body Type (노년기 여성의 체형유형화에 관한 연구)

  • 김인순;성화경
    • Journal of the Korean Society of Clothing and Textiles
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    • v.26 no.1
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    • pp.27-38
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    • 2002
  • This research was to study somatotype characteristics of elderly women and to classify them based on the results. It also analyzed the age distribution of the classified types, and the frequency among the age groups. The subjects of the study were 331 women of the age of 55 fears or older. They were measured on the performing anthropometric and photographic measurements. The samples were classified into 4 different types, and the photographic measure of each front and side view also clustered 4 different types. The results of the research are as follows : The somatotype of elderly women in Korea is most likely to be H-shaped, which shows a slight refraction when viewed from a front. When viewed from a side, an appearance off straight somatotype is common among the age of 70 or younger. However, the age of 70 or older appears to have swayback somatotype. This means that women are likely to reserve their straight body figure from their middle-age until the age of 70. The major somatotype characteristic of old age, a stooped body shape, is more frequently seen as they get older.

Method for Classification of Age and Gender Using Gait Recognition (걸음걸이 인식을 통한 연령 및 성별 분류 방법)

  • Yoo, Hyun Woo;Kwon, Ki Youn
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.41 no.11
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    • pp.1035-1045
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    • 2017
  • Classification of age and gender has been carried out through different approaches such as facial-based and audio-based classifications. One of the limitations of facial-based methods is the reduced recognition rate over large distances, while another is the prerequisite of the faces to be located in front of the camera. Similarly, in audio-based methods, the recognition rate is reduced in a noisy environment. In contrast, gait-based methods are only required that a target person is in the camera. In previous works, the view point of a camera is only available as a side view and gait data sets consist of a standard gait, which is different from an ordinary gait in a real environment. We propose a feature extraction method using skeleton models from an RGB-D sensor by considering characteristics of age and gender using ordinary gait. Experimental results show that the proposed method could efficiently classify age and gender within a target group of individuals in real-life environments.

A study on the prevalence of the idiopathic osteosclerosis in Korean malocclusion patients (한국인 부정교합자의 악골에 발생한 특발성 골경화증의 유병률에 관한 연구)

  • Lee, Seung-Youp;Park, In-Woo;Jang, In-San;Choi, Dong-Soon;Cha, Bong-Kuen
    • Imaging Science in Dentistry
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    • v.40 no.4
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    • pp.159-163
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    • 2010
  • Purpose : This retrospective study was performed to investigate the prevalence of the idiopathic osteosclerosis (IO) in Korean malocclusion patients according to age, sex, and the Angle's classification of malocclusion. Materials and Methods : This study consisted of 2,001 randomly selected patients from the Department of Orthodontics at the Gangneung-Wonju National University Dental Hospital, Korea. The prevalence of IO in Korean malocclusion patients was recorded using their panoramic radiographs, and the following parameters were surveyed; age, sex, and the Angle's classification of malocclusion. The chi-square test was analyzed to determine the statistical significance of differences in the prevalence of IO between age, sex, and the Angle's classification of malocclusion. Results : The prevalence of IO in the jaws was 6.7% in a total of 2,001 examined orthodontic patients. The majority of IO was found in the mandible (96.58%). The 30-39 age group showed the highest prevalence of IO (9.60%). There was a higher prevalence in females (6.89%) than in males (6.45%). The prevalence of IO in Angle Class I group (7.07%) was the most frequent, followed by Angle Class II group (6.72%), and Angle Class III group (6.40%). However, there was no statistical significance in sex and Angle's classification of malocclusion. Conclusion : The prevalence of IO in malocclusion patients showed the differences between various age groups and most of them were found in the mandibular posterior area. However, sex and the type of malocclusion are not to be considered as a contributing factor of IO.

Age classification of emergency callers based on behavioral speech utterance characteristics (발화행태 특징을 활용한 응급상황 신고자 연령분류)

  • Son, Guiyoung;Kwon, Soonil;Baik, Sungwook
    • The Journal of Korean Institute of Next Generation Computing
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    • v.13 no.6
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    • pp.96-105
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    • 2017
  • In this paper, we investigated the age classification from the speaker by analyzing the voice calls of the emergency center. We classified the adult and elderly from the call center calls using behavioral speech utterances and SVM(Support Vector Machine) which is a machine learning classifier. We selected two behavioral speech utterances through analysis of the call data from the emergency center: Silent Pause and Turn-taking latency. First, the criteria for age classification selected through analysis based on the behavioral speech utterances of the emergency call center and then it was significant(p <0.05) through statistical analysis. We analyzed 200 datasets (adult: 100, elderly: 100) by the 5 fold cross-validation using the SVM(Support Vector Machine) classifier. As a result, we achieved 70% accuracy using two behavioral speech utterances. It is higher accuracy than one behavioral speech utterance. These results can be suggested age classification as a new method which is used behavioral speech utterances and will be classified by combining acoustic information(MFCC) with new behavioral speech utterances of the real voice data in the further work. Furthermore, it will contribute to the development of the emergency situation judgment system related to the age classification.

Radiographic evaluation of third molar development in 6- to 24-year-olds

  • Jung, Yun-Hoa;Cho, Bong-Hae
    • Imaging Science in Dentistry
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    • v.44 no.3
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    • pp.185-191
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    • 2014
  • Purpose: This study investigated the developmental stages of third molars in relation to chronological age and compared third molar development according to location and gender. Materials and Methods: A retrospective analysis of panoramic radiographs of 2490 patients aged between 6 and 24 years was conducted, and the developmental stages of the third molars were evaluated using the modified Demirjian's classification. The mean age, standard deviation, minimal and maximal age, and percentile distributions were recorded for each stage of development. A Mann-Whitney U test was performed to test the developmental differences in the third molars between the maxillary and mandibular arches and between genders. A linear regression analysis was used for assessing the correlation between the third molar development and chronological age. Results: The developmental stages of the third molars were more advanced in the maxillary arch than the mandibular arch. Males reached the developmental stages earlier than females. The average age of the initial mineralization of the third molars was 8.57 years, and the average age at apex closure was 21.96 years. The mean age of crown completion was 14.52 and 15.04 years for the maxillary and the mandibular third molars, respectively. Conclusion: The developmental stages of the third molars clearly showed a strong correlation with age. The third molars developed earlier in the upper arch than the lower arch; further, they developed earlier in males than in females.

A Report of Health Status of University Staffs According to the Work Classification

  • Kang Kyounglan;Cho Miran;Kim Byung Sung;Choue Ryowon
    • Journal of Community Nutrition
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    • v.7 no.3
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    • pp.135-140
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    • 2005
  • This study was conducted to evaluate the health status of staff by medical examination data according to the work classification as professional, office worker and laborer in K University in Seoul, Korea. Two thousand four hundred and eighty-four staff (men : 1154, female: 1330) from the university were studied for this report. The anthropometric (height, weight and BMI) and blood pressure (systolic, diastolic) and biochemical parameters (hemoglobin, glucose, cholesterol, AST, ALT) were measured. All groups were calculated using GLM multivariate analysis for three groups after adjustment for age. The average BMI was significantly higher in laborers than professionals and officers after adjustment for age. In blood pressure, especially in SBP, the significant difference was found in females according to the job classification. Blood glucose levels of female laborers were significantly higher than those of officers and professionals. The level of blood total cholesterol of male professionals was significantly higher than those of laborers. The level of blood total cholesterol of female laborers was significantly higher than officers or professionals. Importantly, significant differences were found in BMI, SBP, blood glucose level and cholesterol level of female staff after adjustment for age. These results showed that there were differences in health subjects of staff according to the work classification. This study would provide basic data to prepare the program of health promotion for the college staff according to work classification. Further research is required to discover factors influencing health promotion of staff in colleges.

Diagnostic Classification Scheme in Iranian Breast Cancer Patients using a Decision Tree

  • Malehi, Amal Saki
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.14
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    • pp.5593-5596
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    • 2014
  • Background: The objective of this study was to determine a diagnostic classification scheme using a decision tree based model. Materials and Methods: The study was conducted as a retrospective case-control study in Imam Khomeini hospital in Tehran during 2001 to 2009. Data, including demographic and clinical-pathological characteristics, were uniformly collected from 624 females, 312 of them were referred with positive diagnosis of breast cancer (cases) and 312 healthy women (controls). The decision tree was implemented to develop a diagnostic classification scheme using CART 6.0 Software. The AUC (area under curve), was measured as the overall performance of diagnostic classification of the decision tree. Results: Five variables as main risk factors of breast cancer and six subgroups as high risk were identified. The results indicated that increasing age, low age at menarche, single and divorced statues, irregular menarche pattern and family history of breast cancer are the important diagnostic factors in Iranian breast cancer patients. The sensitivity and specificity of the analysis were 66% and 86.9% respectively. The high AUC (0.82) also showed an excellent classification and diagnostic performance of the model. Conclusions: Decision tree based model appears to be suitable for identifying risk factors and high or low risk subgroups. It can also assists clinicians in making a decision, since it can identify underlying prognostic relationships and understanding the model is very explicit.